Description: This dataset shows a summary of on-system and off-system roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). SLR exposure for each scenario was then summarized for the entire road length. The road segments are sourced from the Florida Department of Transportation Roads Characteristics Inventory (RCI) dataset are from April 2025.
Copyright Text: University of Florida GeoPlan Center, and FDOT
Description: This dataset shows a summary of the Census Bureau's TIGER/Line (2023) roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains.. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). Roads were also analyzed for exposure to flooding from hurricane storm surge zones and FEMA floodplains. Current flood exposure and future SLR flood exposure was then summarized for the entire length of the original road and attributes were added to represent the percentage and feet of flooded roadway per flood scenario. The road segments are sourced from the U.S. Census Bureau's TIGER/Line data (All Lines County-based Shapefiles) this dataset is from December 5th, 2023.Please Note: TIGER Roads segments classified as ramps were not included in the flood analysis. Elevated road segments, such as ramps, are often incorrectly identified as flooded. This is because the inundation models were created using a bare earth model DEM, which represents ground elevations. In cases of elevated roads, the DEM reports the land under the roadway and not the road surface.
Copyright Text: U.S. Department of Commerce, U.S. Census Bureau, Geography Division and University of Florida GeoPlan Center, and FDOT.
Description: This dataset shows a summary of on-system and off-system roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). SLR exposure for each scenario was then summarized for the entire road length. The road segments are sourced from the Florida Department of Transportation Roads Characteristics Inventory (RCI) dataset are from April 2025.
Copyright Text: University of Florida GeoPlan Center, and FDOT
Name: % Local Roadway in 100 & 500-Year Floodplain
Display Field: FULLNAME
Type: Feature Layer
Geometry Type: esriGeometryPolyline
Description: This dataset shows a summary of the Census Bureau's TIGER/Line (2023) roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains.. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). Roads were also analyzed for exposure to flooding from hurricane storm surge zones and FEMA floodplains. Current flood exposure and future SLR flood exposure was then summarized for the entire length of the original road and attributes were added to represent the percentage and feet of flooded roadway per flood scenario. The road segments are sourced from the U.S. Census Bureau's TIGER/Line data (All Lines County-based Shapefiles) this dataset is from December 5th, 2023.Please Note: TIGER Roads segments classified as ramps were not included in the flood analysis. Elevated road segments, such as ramps, are often incorrectly identified as flooded. This is because the inundation models were created using a bare earth model DEM, which represents ground elevations. In cases of elevated roads, the DEM reports the land under the roadway and not the road surface.
Copyright Text: U.S. Department of Commerce, U.S. Census Bureau, Geography Division and University of Florida GeoPlan Center, and FDOT.
Description: This dataset shows a summary of on-system and off-system roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). SLR exposure for each scenario was then summarized for the entire road length. The road segments are sourced from the Florida Department of Transportation Roads Characteristics Inventory (RCI) dataset are from April 2025.
Copyright Text: University of Florida GeoPlan Center, and FDOT
Description: This dataset shows a summary of the Census Bureau's TIGER/Line (2023) roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains.. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). Roads were also analyzed for exposure to flooding from hurricane storm surge zones and FEMA floodplains. Current flood exposure and future SLR flood exposure was then summarized for the entire length of the original road and attributes were added to represent the percentage and feet of flooded roadway per flood scenario. The road segments are sourced from the U.S. Census Bureau's TIGER/Line data (All Lines County-based Shapefiles) this dataset is from December 5th, 2023.Please Note: TIGER Roads segments classified as ramps were not included in the flood analysis. Elevated road segments, such as ramps, are often incorrectly identified as flooded. This is because the inundation models were created using a bare earth model DEM, which represents ground elevations. In cases of elevated roads, the DEM reports the land under the roadway and not the road surface.
Copyright Text: U.S. Department of Commerce, U.S. Census Bureau, Geography Division and University of Florida GeoPlan Center, and FDOT.
Description: This dataset shows a summary of on-system and off-system roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). SLR exposure for each scenario was then summarized for the entire road length. The road segments are sourced from the Florida Department of Transportation Roads Characteristics Inventory (RCI) dataset are from April 2025.
Copyright Text: University of Florida GeoPlan Center, and FDOT
Description: This dataset shows a summary of the Census Bureau's TIGER/Line (2023) roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains.. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). Roads were also analyzed for exposure to flooding from hurricane storm surge zones and FEMA floodplains. Current flood exposure and future SLR flood exposure was then summarized for the entire length of the original road and attributes were added to represent the percentage and feet of flooded roadway per flood scenario. The road segments are sourced from the U.S. Census Bureau's TIGER/Line data (All Lines County-based Shapefiles) this dataset is from December 5th, 2023.Please Note: TIGER Roads segments classified as ramps were not included in the flood analysis. Elevated road segments, such as ramps, are often incorrectly identified as flooded. This is because the inundation models were created using a bare earth model DEM, which represents ground elevations. In cases of elevated roads, the DEM reports the land under the roadway and not the road surface.
Copyright Text: U.S. Department of Commerce, U.S. Census Bureau, Geography Division and University of Florida GeoPlan Center, and FDOT.
Description: This dataset shows a summary of on-system and off-system roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). SLR exposure for each scenario was then summarized for the entire road length. The road segments are sourced from the Florida Department of Transportation Roads Characteristics Inventory (RCI) dataset are from April 2025.
Copyright Text: University of Florida GeoPlan Center, and FDOT
Description: This dataset shows a summary of the Census Bureau's TIGER/Line (2023) roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains.. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). Roads were also analyzed for exposure to flooding from hurricane storm surge zones and FEMA floodplains. Current flood exposure and future SLR flood exposure was then summarized for the entire length of the original road and attributes were added to represent the percentage and feet of flooded roadway per flood scenario. The road segments are sourced from the U.S. Census Bureau's TIGER/Line data (All Lines County-based Shapefiles) this dataset is from December 5th, 2023.Please Note: TIGER Roads segments classified as ramps were not included in the flood analysis. Elevated road segments, such as ramps, are often incorrectly identified as flooded. This is because the inundation models were created using a bare earth model DEM, which represents ground elevations. In cases of elevated roads, the DEM reports the land under the roadway and not the road surface.
Copyright Text: U.S. Department of Commerce, U.S. Census Bureau, Geography Division and University of Florida GeoPlan Center, and FDOT.
Description: This dataset shows a summary of on-system and off-system roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). SLR exposure for each scenario was then summarized for the entire road length. The road segments are sourced from the Florida Department of Transportation Roads Characteristics Inventory (RCI) dataset are from April 2025.
Copyright Text: University of Florida GeoPlan Center, and FDOT
Description: This dataset shows a summary of the Census Bureau's TIGER/Line (2023) roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains.. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). Roads were also analyzed for exposure to flooding from hurricane storm surge zones and FEMA floodplains. Current flood exposure and future SLR flood exposure was then summarized for the entire length of the original road and attributes were added to represent the percentage and feet of flooded roadway per flood scenario. The road segments are sourced from the U.S. Census Bureau's TIGER/Line data (All Lines County-based Shapefiles) this dataset is from December 5th, 2023.Please Note: TIGER Roads segments classified as ramps were not included in the flood analysis. Elevated road segments, such as ramps, are often incorrectly identified as flooded. This is because the inundation models were created using a bare earth model DEM, which represents ground elevations. In cases of elevated roads, the DEM reports the land under the roadway and not the road surface.
Copyright Text: U.S. Department of Commerce, U.S. Census Bureau, Geography Division and University of Florida GeoPlan Center, and FDOT.
Description: This dataset shows a summary of on-system and off-system roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). SLR exposure for each scenario was then summarized for the entire road length. The road segments are sourced from the Florida Department of Transportation Roads Characteristics Inventory (RCI) dataset are from April 2025.
Copyright Text: University of Florida GeoPlan Center, and FDOT
Description: This dataset shows a summary of the Census Bureau's TIGER/Line (2023) roadways exposed to future flooding from sea level rise (SLR) and current flooding from hurricane storm surge and floodplains.. Roads were analyzed for exposure to future flooding under twenty SLR scenarios (every half-foot of SLR, from 0.5-feet to 10-feet of SLR above mean higher high water). Roads were also analyzed for exposure to flooding from hurricane storm surge zones and FEMA floodplains. Current flood exposure and future SLR flood exposure was then summarized for the entire length of the original road and attributes were added to represent the percentage and feet of flooded roadway per flood scenario. The road segments are sourced from the U.S. Census Bureau's TIGER/Line data (All Lines County-based Shapefiles) this dataset is from December 5th, 2023.Please Note: TIGER Roads segments classified as ramps were not included in the flood analysis. Elevated road segments, such as ramps, are often incorrectly identified as flooded. This is because the inundation models were created using a bare earth model DEM, which represents ground elevations. In cases of elevated roads, the DEM reports the land under the roadway and not the road surface.
Copyright Text: U.S. Department of Commerce, U.S. Census Bureau, Geography Division and University of Florida GeoPlan Center, and FDOT.